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首页> 外文期刊>Journal of the Iranian Chemical Society >Developing quantitative structure-retention relationship model to prediction of retention factors of some alkyl-benzenes in nano-LC
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Developing quantitative structure-retention relationship model to prediction of retention factors of some alkyl-benzenes in nano-LC

机译：开发定量结构保留关系模型以预测纳米LC中一些烷基苯的保留因子

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摘要

The present study intends to develop the quantitative structure-retention relationship (QSRR) models to predict the retention factor of some alkyl-benzenes on micro-dispersed sintered nano-diamond (MSND) and silica-gel stationary phases as new and common stationary phase, respectively, in normal-phase HPLC. Genetic algorithm-multiple linear regression (GA-MLR) method employed for implementation of QSRR models. The square of correlation coefficient (R-2) was 0.997 and 0.961, and the SE was 1.06 and 1.93, respectively, for the training and test sets of GA-MLR model on MSND stationary phase. In addition, the R-2 was 0.994 and 0.984, and the SE was 0.01 for both the training and test sets of GA-MLR model on silica-gel stationary phase. The statistical parameters and the result of validation tests of these models confirm the fitness, robustness, and predictability of developed QSRR models. The mean effect analysis on the best models introduced the polarizability as the most significant factor that effects on the retention factor of solutes on both studied stationary phases. This similarity confirms the suggestion of MSND as a common stationary phase for normal-phase HPLC. The developed models enable to predict the retention factor of other alkyl-benzenes on both MSND and silica-gel stationary phases on their applicability domain.
机译：本研究旨在开发定量的结构保留关系（QSRR）模型，以预测微分散的烧结纳米金刚石（MSND）和硅胶固定阶段一些烷基苯的保留因子，如新的和常见的固定相，分别在正常相HPLC中。基于QSRR模型的遗传算法 - 用于实现QSRR模型的多元线性回归（GA-MLR）方法。相关系数（R-2）的平方为0.997和0.961，SE分别为1.06和1.93，用于MSND固定相的GA-MLR模型的训练和测试组。此外，R-2为0.994和0.984，并且SE为硅胶固定相的GA-MLR模型的训练和试验组0.01。这些模型的统计参数和验证测试的结果证实了开发QSRR模型的健身，鲁棒性和可预测性。对最佳模型的平均效果分析将极化性引入了最重要的因素，这些因素对溶质对静止阶段的溶质的保留因子的影响。这种相似性证实了MSND的建议作为正常相HPLC的常见固定相。开发的模型使得能够在其适用性域上预测MSND和二氧化硅凝胶固定相的其他烷基苯的保留系数。

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